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This example demonstrates how to load and summarize a CSV dataset using D3.js within a React application. It displays file size, row count, and column names by fetching the raw CSV text and parsing it with `d3.csvParse`. The page also renders basic SVG shapes—a circle, rectangle, line, and text—to illustrate static SVG output. The React component uses the `useRef` and `useEffect` hooks alongside `d3.select` to update the DOM.

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This example displays a dataset summary for a study focus log, showing the file size, row count, and column count in a styled HTML container. It loads a CSV file from a GitHub gist using D3 v7’s `d3.text` and `d3.csvParse` functions, then updates the DOM with the computed statistics. The React-based shell, using `ReactDOM.createRoot` and `useEffect`, integrates a D3 selection to render a simple message, though the primary data display relies on vanilla JavaScript embedded within the HTML file.

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This example summarizes a study focus dataset by displaying its file size, row count, and column count. The React app uses `fetch` to retrieve a CSV file and `d3.csvParse` to parse it, then renders the summary stats in styled HTML elements alongside simple SVG shapes—a circle and a rectangle—for visual interest. The code mixes a modern React component with an older vanilla HTML/D3 script in `index.html`, both relying on D3 v7 for data processing.

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This example displays a summary of a study-focus dataset, presenting the file size, row count, and column count. It retrieves a CSV file from a remote GitHub gist and parses it using `d3.text` and `d3.csvParse`. The React framework, with `index.jsx` utilizing `useRef` and `useEffect`, manages the page layout, while the embedded HTML script uses the `d3.v7` library to fetch and process the data.

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This example displays a study focus dataset summary, showing the file size, row count, and column count from a remote CSV file. It uses React’s `useState` and `useEffect` hooks to fetch the data and `d3.csvParse` to parse the CSV text. The visualization renders a static SVG containing a circle and rectangle with light fills and black strokes, alongside the computed metrics. The code logs the file size, rows, and columns to the browser console.

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This example displays a simple dataset summary for an ICE-5 study focus log, showing the file size, row count, and column count. It loads a CSV file from a GitHub gist using d3.text and parses it with d3.csvParse, then updates HTML paragraph elements with the computed metrics. The React component uses the useRef and useEffect hooks alongside d3.select to render a static message. The visualization provides a quick overview of the data structure rather than a graphical chart, serving as a basic data-loading demonstration.

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This example displays a summary of a study focus dataset, showing the file size in kilobytes, row count, and column count from a remote CSV file. The React app uses `d3.csvParse` to parse the fetched data and `useState` and `useEffect` hooks to manage the asynchronous loading process. It renders the metrics as text alongside a static SVG containing a lightblue circle and a lightgreen rectangle, demonstrating basic SVG shape rendering within a styled card layout.

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This example demonstrates data loading and basic summary statistics using D3.js within an HTML page. It fetches a remote CSV file, displays the file size, row count, and column count, and generates a simple SVG bar chart representing the first ten rows. The visualization uses D3's `csvParse` method to parse the dataset and `select`/`selectAll`/`join` APIs to create and style the bars and labels. Minimal styling and layout are achieved with plain CSS.